The invention relates generally to signal analysis systems or test and measurement systems, and more particularly to a computer-based system and method for analyzing order components of a signal generated by a physical system, e.g., a mechanical system containing one or more rotating elements.
Scientists and engineers often use test and measurement systems and data acquisition systems to perform a variety of functions, including laboratory research, process monitoring and control, data logging, analytical chemistry, test and analysis of physical phenomena and analysis or control of mechanical or electrical machinery, to name a few examples. One example of hardware to implement such measuring systems is a computer-based measurement system or data acquisition (DAQ) system. Another example of a measurement system is a dedicated instrument, such as a dedicated oscilloscope or signal analyzer.
A measurement system typically may include transducers for measuring and/or providing electrical signals, signal conditioning hardware which may perform amplification, isolation and/or filtering, and measurement or DAQ hardware for receiving digital and analog signals and providing them to a processing system, such as a processor or personal computer. The computer-based measurement system or dedicated instrument may further include analysis hardware and software for analyzing and appropriately displaying the measured data.
One example where measurement and data acquisition systems are used is in the field of rotating machinery analysis. This involves the analysis of physical signals such as vibration or acoustic signals from a rotating machine. A physical signal acquired from a rotating machine may be sampled or digitized. Typically, samples of the physical signal are equidistant in time, i.e., are acquired at constant time increments. However, rotating machines generate signals which are periodic with respect to shaft rotation, i.e., rotation angle of an underlying rotating element (e.g. a crank shaft of an engine). These rotation-periodic signals are referred to herein as order components. When the rotation rate changes in time, the order components change correspondingly in frequency. For example, when the rotation rate increases, the order components increase in frequency. Thus, a traditional analysis method such as the Discrete Fourier Transform (DFT), when applied to the physical signal, displays a frequency smearing of order components. The frequency smearing makes it very difficult to derive meaningful information about the order components. Thus, traditional signal analysis methods such as the Fourier Transform of the time domain input signal are not well suited for analyzing order components generated by rotating machines.
In order to better analyze the performance and characteristics of rotating machines, certain prior art systems convert the time-samples, i.e., the samples of the physical signal which are equally spaced in time, to angle-samples, i.e., samples which are equally spaced in shaft angle. For example, U.S. Pat. No. 4,912,661 assigned to Hewlett-Packard discloses an interpolation method for estimating angle-samples from time-samples. The method disclosed in U.S. Pat. No. 4,912,661 performs an interpolation of the time domain signal, followed by a re-sampling, in order to produce samples equally spaced with respect to shaft angle. The order components may then be analyzed by performing a traditional analysis method such as the Discrete Fourier Transform on the angle-samples. The process of U.S. Pat. No. 4,912,661 uses a piece-wise polynomial curve fit to smooth data prior to re-sampling. However, this approach may result in discontinuities at boundaries of the polynomial pieces or segments. One prior art system known as the Vold-Kalman filter allows the user to track the frequency of an order component given a sufficiently accurate model for the physical signal. The Vold-Kalman filter performance may be strongly sensitive to model accuracy. In other words, the tracking performance is likely to be degraded when an inaccurate signal model is supplied to the filter. Furthermore, the Vold-Kalman filter provides no mechanism for the user to evaluate the accuracy of the frequency tracking for an order component.
Therefore, there exists a need for a system and method which can more accurately and robustly analyze order components of a physical signal, and reconstruct desired order components from the time domain in the angle domain.
One embodiment of the present invention comprises a computer-based method for analyzing a signal X acquired from a physical system with a rotating element. In one embodiment, a tachometer signal may be received, where the tachometer signal includes a first plurality of samples, and where the tachometer signal includes rotation speed information for the rotating element. The tachometer signal may be generated by a tachometer, where the tachometer measures rotation of the rotating element, and generates a fixed number of pulses per revolution. In one embodiment, an analog to digital converter (ADC), also referred to as a digitizer, may be used to digitize the tachometer pulse signal to generate a discrete tachometer signal. Then, software edge detection may be performed on the discrete tachometer signal to generate a time sequence corresponding to pulse arrival times, where the time sequence indicates each time the rotating element has rotated a certain angle. In other words, the time sequence contains time values of substantially equal angle interval. In an embodiment where the tachometer signal is a Transistor-Transistor Logic (TTL) level compatible square wave, the time series of pulse arrival time may be determined directly from the tachometer signal, e.g., using a timer/counter, and thus the time sequence may be determined without having to digitize and perform software edge detection on the tachometer signal. A first digital interpolation filter may then be applied to the equal angle time sequence to generate a modified a modified time sequence. In other words, the first digital interpolation filter may be used to smooth and/or increase the resolution of the time sequence. In a preferred embodiment, the first digital interpolation filter may be a finite impulse response (FIR) filter, such as, for example, a Cascade Integrator-Comb (CIC) filter. The modified time sequence includes time values for the rotating element at substantially equal angle increments, e.g., of a desired resolution. In other words, the original time sequence may be at a first angular resolution, and the first digital interpolation filter may be applied to the original time sequence to generate the modified time sequence at a second angular resolution, where the second angular resolution is higher than the first angular resolution. Thus, in one embodiment, the determined time sequence includes time values at the second (e.g., higher) angular resolution. In one embodiment, the time sequence may be stored, e.g., in a storage medium, for later use.
A digital data signal may be received, where the digital data signal includes a second plurality of samples, and where the digital data signal includes data for the rotating element at substantially equal time increments. In one embodiment, the digital data signal may be generated by using an analog-to-digital converter (ADC) to digitize a received analog data signal from a sensor, where the sensor measures an attribute of the rotating element. In other words, the ADC may digitizing the analog data signal to generate the digital data signal. A second digital interpolation filter may be applied to the digital data signal to generate a modified data signal. In other words, as described above, the second digital interpolation filter may be applied to the digital data signal to smooth and/or increase the resolution of the digital data signal. In a preferred embodiment, the second digital interpolation filter may also be a finite impulse response (FIR) filter.
The modified data signal may then be re-sampled using the determined time sequence to generate an angle domain data signal, where the angle domain data signal includes data signal values at substantially equal angle increments. The angle domain data signal may then be usable to analyze the physical system. In one embodiment, a Fast Fourier Transform (FFT) may be performed on the angle domain signal to generate order spectrum information which may be usable to analyze the physical system.
In one embodiment, the angle domain data signal may be output. For example, the angle domain data signal may be output to a storage medium and/or a display device for display, e.g., a computer monitor or printer.
Thus, various embodiments of the present invention may be used to convert time domain data related to a rotating element of a physical system to angle domain data at substantially equal angular increments. Additionally, the present method is substantially more accurate and more flexible than prior art methods.